A probabilistic time geographic approach to quantifying seabird‐vessel interactions

• Published in: Animal conservation 2024-12, Vol.27 (6), p.816-829
• Main Authors: Rutter, J. D., Borrelle, S. B., Bose, S., Carneiro, A. P.B., Clark, B. L., Debski, I., Elliott, G., Fischer, J. H., Walker, K., Pittman, S. J.
• Format: Article
• Language: English
• Subjects: Aquatic birds; Birds; Bycatch; Conservation; Diomedea antipodensis; Fisheries; Fishing vessels; High seas; Longline fishing; Longliners; Marine fish; Pelagic fisheries; Prisms; Sea vessels; Seabirds; Seabird‐Fishery Interactions; Space–Time Prism; Statistical analysis; Time Geography; Time measurement; Uncertainty
• ISSN: 1367-9430; 1469-1795
• DOI: 10.1111/acv.12961

Accounting for uncertainty is essential for precautionary approaches to managing seabird bycatch in commercial fisheries. However, there is no existing mechanism to explicitly quantify the uncertainty of seabird‐vessel interactions (i.e. co‐occurrence in space and time). Here we develop a time geographic method to measure the probability of individual birds encountering (co‐occurring within 30 km) and attending (within 5 km) individual fishing vessels. The approach involves creating voxel‐based probabilistic space–time prisms (PSTPs) to model the movements of individual birds and vessels, with trajectory data from bird‐borne GPS devices and vessel Automatic Identification Systems (AIS). We intersected these PSTPs to quantify the probability of interaction between bird‐vessel pairs over time and space. We demonstrate the approach with a case study of interactions of Endangered Toroa (Antipodean Albatross; Diomedea antipodensis antipodensis) with pelagic longline vessels in part of the South Pacific high seas. We found 15 vessels within 150 km and 3 h of two birds, yet interaction occurred with only two of those vessels. We visualised the probability of encounter and attendance over time and space and determined that interactions lasted several hours each (up to 6.2–14.1 h attendance, 20.8–26.1 h encounter for one bird‐vessel pair). Our time geographic approach adds to existing tools to quantify seabird bycatch risk by providing an explicit measure of uncertainty of seabird‐vessel interactions. We provide a flexible methodological pathway and R scripts, the application of which would allow managers to estimate interaction probability for multiple marine species and fisheries, including those with lower‐resolution positional datasets. Putanga Mātua te whakaaro ki te matawaenga ngā arunga whakatūpato ki te whakahaere i te hao pokerehū o te manu ā‐tai i te ahu‐hī ika. Heoi anō, kāore tonu he ara i tēnei wā e taea pū nei te ine i te matawaenga o ngā pāhekoheko i waenga i te manu ā‐tai me te kaipuke (ko te tūtaki tahi i taua wāhi, i taua wā tonu tērā). Ka whakawhanakehia he tikanga e aro ana ki te wā me te wāhi kia ine ai te pāpono o ngā manu ā‐tai takitahi e tūpono atu ai (ka tae kia 30 manomita te tata) e rokohanga atu (kia 5 manomita te tata) ki tētahi kaipuke hī ika. Kei te aronga nei he poro pāpono wā‐wāhi tūāpapa tongiiti ahutoru (PTSPs) kia whakatakune ngā nekehanga o ngā manu takitahi me ngā kaipuke, me te raraunga ara whiu mai i ngā pūrere GPS e kawea an